using darknet yolov3 - problems with bounding boxes about deep_sort_yolov3 HOT 1 CLOSED

solved:

def yolo_results_to_boxes(yolo_results):
boxs = [x[2] for x in yolo_results]
results = []
for box in boxs:
x, y, w, h = box
new_x = int(x - (w/2))
new_y = int(y - (h/2))
new_w = int(w)
new_h = int(h)
# print('{}, {}, {}, {}'.format(x, y, w, h))
# print('{} -> {}'.format(x, new_x))
# print('{} -> {}'.format(y, new_y))
# print('{} -> {}'.format(w, new_w))
# print('{} -> {}'.format(h, new_h))
# print('{}, {}, {}, {}'.format(new_x, new_y, new_w, new_h))
results.append([new_x, new_y, new_w, new_h])
return results

the output of performDetect can now directly replace the keras version without affecting functionality

from deep_sort_yolov3.